flan-t5-rouge-durga-2

This model is a fine-tuned version of google/flan-t5-base on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0015
• Rouge1: 0.4073
• Rouge2: 0.3631
• Rougel: 0.4076
• Rougelsum: 0.4081

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.0003
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
3.6674	1.0	85	1.9307	0.2328	0.1210	0.2076	0.2079
2.8171	2.0	170	1.5796	0.2548	0.1280	0.2250	0.2246
2.1491	3.0	255	1.2905	0.2604	0.1445	0.2384	0.2376
1.4061	4.0	340	1.0662	0.2631	0.1474	0.2447	0.2446
1.0805	5.0	425	0.8724	0.2631	0.1479	0.2417	0.2417
1.4852	6.0	510	0.7009	0.2861	0.1735	0.2718	0.2716
1.7677	7.0	595	0.5283	0.2842	0.1876	0.2710	0.2708
0.5014	8.0	680	0.3990	0.3142	0.2208	0.3011	0.3015
1.5085	9.0	765	0.3122	0.3371	0.2522	0.3254	0.3255
0.7696	10.0	850	0.2204	0.3537	0.2695	0.3423	0.3418
0.7834	11.0	935	0.1808	0.3596	0.2813	0.3492	0.3491
0.5238	12.0	1020	0.1300	0.3723	0.3043	0.3674	0.3674
0.4623	13.0	1105	0.0940	0.3754	0.3166	0.3716	0.3716
0.3645	14.0	1190	0.0679	0.3752	0.3149	0.3715	0.3727
0.319	15.0	1275	0.0466	0.3902	0.3372	0.3888	0.3895
0.1117	16.0	1360	0.0375	0.3945	0.3409	0.3928	0.3932
0.1975	17.0	1445	0.0274	0.4010	0.3537	0.4002	0.4007
0.2396	18.0	1530	0.0254	0.3985	0.3525	0.3976	0.3976
0.3832	19.0	1615	0.0156	0.3976	0.3482	0.3963	0.3970
0.2136	20.0	1700	0.0118	0.3998	0.3524	0.3996	0.4000
0.1789	21.0	1785	0.0115	0.4022	0.3568	0.4020	0.4027
0.0027	22.0	1870	0.0082	0.4047	0.3593	0.4051	0.4057
0.2978	23.0	1955	0.0070	0.4028	0.3578	0.4032	0.4036
0.1529	24.0	2040	0.0053	0.4075	0.3625	0.4078	0.4083
0.0584	25.0	2125	0.0044	0.4073	0.3621	0.4075	0.4081
0.0669	26.0	2210	0.0030	0.4071	0.3625	0.4073	0.4078
0.2968	27.0	2295	0.0021	0.4073	0.3625	0.4074	0.4080
0.072	28.0	2380	0.0018	0.4073	0.3625	0.4074	0.4080
0.1676	29.0	2465	0.0016	0.4073	0.3631	0.4076	0.4081
0.1567	30.0	2550	0.0015	0.4073	0.3631	0.4076	0.4081

Framework versions

• Transformers 4.44.2
• Pytorch 2.4.0+cu121
• Datasets 3.0.0
• Tokenizers 0.19.1